Python GraphProperties.linewidth_2方法代码示例

# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import linewidth_2 [as 别名]
    def run_day_of_month_analysis(self, strat):
        from pythalesians.economics.seasonality.seasonality import Seasonality
        from pythalesians.timeseries.calcs.timeseriescalcs import TimeSeriesCalcs

        tsc = TimeSeriesCalcs()
        seas = Seasonality()
        strat.construct_strategy()
        pnl = strat.get_strategy_pnl()

        # get seasonality by day of the month
        pnl = pnl.resample('B').mean()
        rets = tsc.calculate_returns(pnl)
        bus_day = seas.bus_day_of_month_seasonality(rets, add_average = True)

        # get seasonality by month
        pnl = pnl.resample('BM').mean()
        rets = tsc.calculate_returns(pnl)
        month = seas.monthly_seasonality(rets)

        self.logger.info("About to plot seasonality...")
        gp = GraphProperties()
        pf = PlotFactory()

        # Plotting spot over day of month/month of year
        gp.color = 'Blues'
        gp.scale_factor = self.scale_factor
        gp.file_output = self.DUMP_PATH + strat.FINAL_STRATEGY + ' seasonality day of month.png'
        gp.title = strat.FINAL_STRATEGY + ' day of month seasonality'
        gp.display_legend = False
        gp.color_2_series = [bus_day.columns[-1]]
        gp.color_2 = ['red'] # red, pink
        gp.linewidth_2 = 4
        gp.linewidth_2_series = [bus_day.columns[-1]]
        gp.y_axis_2_series = [bus_day.columns[-1]]

        pf.plot_line_graph(bus_day, adapter = 'pythalesians', gp = gp)

        gp = GraphProperties()

        gp.scale_factor = self.scale_factor
        gp.file_output = self.DUMP_PATH + strat.FINAL_STRATEGY + ' seasonality month of year.png'
        gp.title = strat.FINAL_STRATEGY + ' month of year seasonality'

        pf.plot_line_graph(month, adapter = 'pythalesians', gp = gp)

        return month

# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import linewidth_2 [as 别名]
    def g10_line_plot_cpi(self, start_date, finish_date):
        today_root = datetime.date.today().strftime("%Y%m%d") + " "
        country_group = 'g10-ez'
        cpi = self.get_CPI_YoY(start_date, finish_date, country_group)

        from pythalesians.graphics.graphs.plotfactory import PlotFactory
        from pythalesians.graphics.graphs.graphproperties import GraphProperties

        gp = GraphProperties()
        pf = PlotFactory()

        gp.title = "G10 CPI YoY"
        gp.units = '%'
        gp.scale_factor = 3
        gp.file_output = today_root + 'G10 CPI YoY ' + str(gp.scale_factor) + '.png'
        cpi.columns = [x.split('-')[0] for x in cpi.columns]
        gp.linewidth_2 = 3
        gp.linewidth_2_series = ['United States']

        pf.plot_generic_graph(cpi, type = 'line', adapter = 'pythalesians', gp = gp)

# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import linewidth_2 [as 别名]
    def g10_line_plot_une(self, start_date, finish_date):
        today_root = datetime.date.today().strftime("%Y%m%d") + " "
        country_group = 'g10-ez'
        une = self.get_UNE(start_date, finish_date, country_group)

        from pythalesians.graphics.graphs.plotfactory import PlotFactory
        from pythalesians.graphics.graphs.graphproperties import GraphProperties

        gp = GraphProperties()
        pf = PlotFactory()

        gp.title = "G10 Unemployment Rate (%)"
        gp.units = '%'
        gp.scale_factor = Constants.plotfactory_scale_factor
        gp.file_output = today_root + 'G10 UNE ' + str(gp.scale_factor) + '.png'
        une.columns = [x.split('-')[0] for x in une.columns]
        gp.linewidth_2 = 3
        gp.linewidth_2_series = ['United States']

        pf.plot_generic_graph(une, type = 'line', adapter = 'pythalesians', gp = gp)

# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import linewidth_2 [as 别名]
    def g10_line_plot_gdp(self, start_date, finish_date):
        today_root = datetime.date.today().strftime("%Y%m%d") + " "
        country_group = 'g10-ez'
        gdp = self.get_GDP_QoQ(start_date, finish_date, country_group)

        from pythalesians.graphics.graphs.plotfactory import PlotFactory
        from pythalesians.graphics.graphs.graphproperties import GraphProperties

        gp = GraphProperties()
        pf = PlotFactory()

        gp.title = "G10 GDP"
        gp.units = 'Rebased'
        gp.scale_factor = Constants.plotfactory_scale_factor
        gp.file_output = today_root + 'G10 UNE ' + str(gp.scale_factor) + '.png'
        gdp.columns = [x.split('-')[0] for x in gdp.columns]
        gp.linewidth_2 = 3
        gp.linewidth_2_series = ['United Kingdom']

        from pythalesians.timeseries.calcs.timeseriescalcs import TimeSeriesCalcs
        tsc = TimeSeriesCalcs()
        gdp = gdp / 100
        gdp = tsc.create_mult_index_from_prices(gdp)
        pf.plot_generic_graph(gdp, type = 'line', adapter = 'pythalesians', gp = gp)

# 需要导入模块: from pythalesians.graphics.graphs.graphproperties import GraphProperties [as 别名]
# 或者: from pythalesians.graphics.graphs.graphproperties.GraphProperties import linewidth_2 [as 别名]
        df_event_times.index = df_event_times.index.tz_localize(utc_time)    # work in UTC time

        from pythalesians.economics.events.eventstudy import EventStudy

        es = EventStudy()

        # work out cumulative asset price moves moves over the event
        df_event = es.get_intraday_moves_over_custom_event(df, df_event_times)

        # create an average move
        df_event['Avg'] = df_event.mean(axis = 1)

        # plotting spot over economic data event
        gp = GraphProperties()
        gp.scale_factor = 3

        gp.title = 'USDJPY spot moves over recent NFP'

        # plot in shades of blue (so earlier releases are lighter, later releases are darker)
        gp.color = 'Blues'; gp.color_2 = []
        gp.y_axis_2_series = []
        gp.display_legend = False

        # last release will be in red, average move in orange
        gp.color_2_series = [df_event.columns[-2], df_event.columns[-1]]
        gp.color_2 = ['red', 'orange'] # red, pink
        gp.linewidth_2 = 2
        gp.linewidth_2_series = gp.color_2_series

        pf = PlotFactory()
        pf.plot_line_graph(df_event * 100, adapter = 'pythalesians', gp = gp)